Modeling the fat tails of size fluctuations in organizations
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Invited at Physics of Social Complexity (PoSCo), Pohang, Korea, January 28 2015. Presenting the paper by Mondani, Holme, Liljeros (2014) http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0100527
Modeling the fat tails of size fluctuations in organizations
Mondani H, Holme P, Liljeros F (2014) Fat-Tailed
Fluctuations in the Size of Organizations: The Role of
Social Influence. PLoS ONE 9(7): e100527.
Modeling the
fat tails of size
fluctuations in
organizations
Petter Holme
Mondani H, Holme P, Liljeros F (2014) Fat-Tailed
Fluctuations in the Size of Organizations: The Role of
Social Influence. PLoS ONE 9(7): e100527.
Modeling the
fat tails of size
fluctuations in
organizations
Petter Holme
Local trade unions in Sweden, 1880–1939
-Long quiet periods
-Large jumps
F Liljeros, The complexity of social organizing, Ph.D. thesis 2001.
Typical data: time series of
sizes (not join / quit numbers)
Examples
Local trade unions in Sweden, 1880–1939
F Liljeros, The complexity of social organizing, Ph.D. thesis 2001.
Examples
Local trade unions in Sweden, 1880–1939
F Liljeros, The complexity of social organizing, Ph.D. thesis 2001.
Examples
Growth rate US firms
Buldyrev & al., J Phys I France 7 (1997), 635–650.
Examples
Growth rate Italian firms
Bottazzi, Secchi, Physica A 324 (2003), 213–219.
Examples
The SAF model
Assumptions
-N individuals connected in a network
-G organizations
-Each time step an agent changes
organization with probability:
Schwartzkopf, Axtell, Farmer, arxiv:1004.5397.
The SAF model
Assumptions
-N individuals connected in a network
-G organizations
-Each time step an agent changes
organization with probability:
Claims the network is
the key (still trying
just one topology)...
Schwartzkopf, Axtell, Farmer, arxiv:1004.5397.
The SAF model
Assumptions
-N individuals connected in a network
-G organizations
-Each time step an agent changes
organization with probability:
Claims the network is
the key (still trying
just one topology)...
Non-equilibrium...
Schwartzkopf, Axtell, Farmer, arxiv:1004.5397.
The SAF model
Assumptions
-N individuals connected in a network
-G organizations
-Each time step an agent changes
organization with probability:
Claims the network is
the key (still trying
just one topology)...
Non-equilibrium...
Hidden parameters...
Schwartzkopf, Axtell, Farmer, arxiv:1004.5397.
Our extended SAF model
Additional assumptions
-Trying different networks
-Organization cannot die (if the last person leaves
a new person joins)
-Attachment probability:
Conclusions
-The SAF model works and it is independent of the network
topology (it just needs a (strongly connected giant
component).
-The contextual influence parameter makes a difference and
can cause the loss of tentity.